Marketing Analytics

Understand the customer. How likely a customer is to purchase, how much a customer will spend, and a relationship with the business. Big Data technologies and data science can fundamentally increase the impact of marketing. Whether you run traditional business to cutting edge technology, data science in marketing will ensure improved marketing ROI.

Human Capital Analytics

Keeping organizations competitive, productive, and efficient ultimately depends on employees. Hiring, retaining, and maintaining a talented workforce is perhaps the most important responsibility of an organization. Human Capital Analytics improves hiring, retaining, and encouraging talent development to ensure organizations succeed.

Our Expertise

Understanding the behavior of moving data has a wide range of applications from nuclear physics and astronomy to counterterrorism and consumer applications. Predicting the location and behavior of data and drawing meaningful conclusions from their motion is conceptually and mathematically challenging. Many theoretical approaches have been developed over the years, and understanding which techniques are best applied to a particular problem is more art than science. For example, consider a set of ships moving on the surface of the ocean. Embedded in the movements of these ships is a whole host of information about the behaviors and intentions of their owners, captains and crews. Why does one vessel take a seemingly inefficient route between two places in perfectly good weather? Does it want to avoid being seen by other ships? Why do two fishing vessels from different countries rendezvous on the open ocean? Are they illegally exchanging their catch, or engaged in human trafficking? Why does a cruise ship's movements closely follow the wind and ocean currents? Is it adrift and in distress?

The techniques used to analyze objects in motion depend on the information sought. Analyze data scientists bring a range of mathematical and algorithmic approaches to motion analytics, including:

Graph Theoretical and Network Techniques

Sometimes motion data is best understood as a collection of route and destinations (edges and vertices). Graph theory is a rich mathematical discipline with established solutions to many common problems such as connectedness, path finding, distances and probabilistic prediction. Interconnectedness in human relationships (sometimes called social network analysis, but not just applied to applications like Facebook and Twitter) can also be explored effectively through graph theoretical techniques.

Geometric and Pattern Matching Techniques

Sometimes motion is expressed in regular, predictable or distinctive mathematical or geometric patterns. A fishing trawler might leave port, cast its nets in a particular manner, retrieve them at a later time and return to its home port whereas a ferry may travel back and forth between two destinations in a straight line, never deviating from its pattern. When drawn out in time series or other projections, these ships create unique geometric patterns. Shape and object recognition techniques, series pattern detection and genetic algorithms help us understand, organize and classify this kind of motion.

Machine Learning Techniques

Machine learning techniques help make sense of complex, unorganized and seemingly random data sets. Clustering identifies data elements that share a common set of features or properties. Correlation tells us whether some features of data (for example, the size or class of ship) help us predict other features (such as its speed or location). Dimensionality reduction helps us reduce the data search space to focus on only those pieces of information that matter. The most powerful techniques, prediction techniques, tell us what an object in motion should do based on past behavior as well as whether it is behaving outside the norm.

Knowledge Management taken to the next level using advanced data science analytics. Using text analysis algorithms from named entity extraction to ontological classification, your organization can leverage the digital knowledge created by your employees over the last decades to ensure it stays productive and cutting edge.

Text Analytics

Knowledge Management taken to the next level using advanced data science. Using text analysis algorithms including named entity extraction and ontological classification, your organization can leverage the digital knowledge created by your employees over the last decades to ensure it stays productive and cutting edge.

How it can help your organization

Mitigate risks of retiring workforce and employee turnover

Leverage analytics to grow operational capability

Ensure leadership and employees alike have access to the most current and relevant information

History and Challenges

Digital Knowledge Analytics algorithms were originally designed to build a next-generation intelligence
collection and analysis grid to support ongoing intelligence
services. In building these algorithms it quickly became apparent that extracting meaningful
intelligence from open source and unstructured collections presented several challenges includingunique
lexicon(s) and set(s) of actors and frequent interleaving of human readable text and
computer-represented data, such as source code. Working through these and other challenges one by one it quickly became apparent how useful these tools could become for any organization. Analyze developed a simple approach to tailor these algorithms to businesses and government organizations archives and historic documents to help address a growing need to mitigate knowledge and experience loss that occurs from a retiring workforce and employee turnover.

Data Management

Terra and petabytes of data present unique data management challenges. While it has become relatively inexpensive to buy flash and hard drive space it remains difficult to understand how to structure hardware, where to store information, and how frequently to index and precompute data.

Our Expertise

With more than 25 years combined experience in distributed computing and parallel processing, Analyze data and computer scientists help organizations match the appropriate hardware and software with their long and short term strategy and needs. Analyze brings extensive experience implementing solutions like the following within the Fortune 100 and the largest government agencies.

Data management determines data value

The basic principle of money management used in purchasing a home or opening a savings account apply to data management: management determines quantity and access. Not all data is created equal and it is important to have immediate access to data needed now while data that will only be valuable in the future can be collected and stored. Analyze helps organizations decide which data to store where and how to ensure access to it when it matures and becomes most valuable.

Choosing which data to keep

Analyze provides recommendations on which data will provide organizations the most lift and which data is not worth the investment.

Choosing where to keep data

The decision on where to keep data is influenced by cost and capability. There are many different database solutions optimized for different types of data, and there are as many hardware and cloud solutions to compare. Analyze helps organizations understand the pros and cons to each solution.

Determining when data is valuable

In the same way that the value of weather forecasts depends on the date observed, the value of data depends on the timing of the analytics.

Ensuring access to the right data

Analyze helps organizations implement the right named entity recognition and ontological classification tools to ensure employees can leverage organizations' intellect and experience. These tools go beyond indexing and search to provide the most relevant and comprehensive reach into previous reports, social network posts, emails, contracts, articles, and other data available.

the process powering our data science

Under the Hood: the process powering our data science

1. CAPTURE

Existing data is collected and new data is captured on the web, on the road or over the ocean.

2. ORGANIZE

Data is organized into a format permitting visualization and analysis beyond the limits of traditional database platforms. A custom platform (e.g. hadoop, cassandra, NOSQL, etc.) will be assembled to best fit clients' needs.

3. VISUALIZE

Leveraging the most trusted and reliable open source infrastructure, we use Phosphorus, our proprietary platform, to visualize your data to support data capture, organization, analysis, and ultimately provide the justification you need to act.

4. ANALYZE

Whether your organization needs basic business intelligence (count, mean, regression, and log) or the most advanced data analytics, we provide the analysis that you need. Our advanced capabilities span from graph theoretical and network techniques to machine learning and geometric pattern matching techniques and beyond.

5. IMPLEMENT

With experience working for the most advanced government agencies to the Fortune 100, we understand that the analytics must support decision making for business objectives and organizational missions. We team with industry experts to ensure you receive data driven recommendations that meet your mission or objective. We will then help you design the best method to implement these recommendations within your organization, from setting new or configuring your existing hardware, installing new software, or writing new algorithm and software code tailored to your organization.